Determining and forecasting end of life for an implantable medical device having a rechargeable battery

ABSTRACT

An algorithm programmed into the control circuitry of a rechargeable-battery Implantable Medical Device (IMD) is disclosed that can quantitatively forecast and determine the timing of an early replacement indicator (tEOLi) and an IMD End of Life (tEOL). These forecasts and determinations of tEOLi and tEOL occur in accordance with one or more parameters having an effect on rechargeable battery capacity, such as number of charging cycles, charging current, discharge depth, load current, and battery calendar age. The algorithm consults such parameters as stored over the history of the operation of the IMD in a parameter log, and in conjunction with a battery capacity database reflective of the effect of these parameters on battery capacity, determines and forecasts tEOLi and tEOL Such forecasted or determined values may also be used by a shutdown algorithm to suspend therapeutic operation of the IMD.

CROSS REFERENCE TO RELATED APPLICATIONS

This is a non-provisional of U.S. provisional patent application Ser.No. 61/928,391, filed Jan. 16, 2014, to which priority is claimed, andwhich is incorporated herein by reference in its entirety.

This application is related to U.S. provisional patent applications61/928,342 and 61/928,352, both filed Jan. 16, 2014, which are bothincorporated herein by reference in their entireties.

FIELD OF THE INVENTION

This application relates to the field of implantable medical devices,and in particular to rechargeable battery implantable medical devices.

BACKGROUND

Implantable stimulation devices deliver electrical stimuli to nerves andtissues for the therapy of various biological disorders, such aspacemakers to treat cardiac arrhythmia, defibrillators to treat cardiacfibrillation, cochlear stimulators to treat deafness, retinalstimulators to treat blindness, muscle stimulators to producecoordinated limb movement, spinal cord stimulators to treat chronicpain, cortical and deep brain stimulators to treat motor andpsychological disorders, and other neural stimulators to treat urinaryincontinence, sleep apnea, shoulder subluxation, etc. The descriptionthat follows will generally focus on the use of the invention within aSpinal Cord Stimulation (SCS) system, such as that disclosed in U.S.Pat. No. 6,516,227. However, the present invention may findapplicability with any implantable medical device or in any implantablemedical device system.

An SCS system typically includes an Implantable Pulse Generator (IPG) 10shown in plan and cross-sectional views in FIGS. 1A and 1B. The IPG 10includes a biocompatible device case 30 that holds the circuitry andbattery 36 necessary for the IPG to function. The IPG 10 is coupled toelectrodes 16 via one or more electrode leads 14 that form an electrodearray 12. The electrodes 16 are configured to contact a patient's tissueand are carried on a flexible body 18, which also houses the individuallead wires 20 coupled to each electrode 16. The lead wires 20 are alsocoupled to proximal contacts 22, which are insertable into leadconnectors 24 fixed in a header 28 on the IPG 10, which header cancomprise an epoxy for example. Once inserted, the proximal contacts 22connect to header contacts 26, which are in turn coupled by feedthroughpins 34 through a case feedthrough 32 to circuitry within the case 30.

In the illustrated IPG 10, there are thirty-two lead electrodes (E1-E32)split between four leads 14, with the header 28 containing a 2×2 arrayof lead connectors 24. However, the number of leads and electrodes in anIPG is application specific and therefore can vary. In a SCSapplication, the electrode leads 14 are typically implanted proximate tothe dura in a patient's spinal cord, and when a four-lead IPG 10 isused, these leads are usually split with two on each of the right andleft sides of the dura. The proximal electrodes 22 are tunneled throughthe patient's tissue to a distant location such as the buttocks wherethe IPG case 30 is implanted, at which point they are coupled to thelead connectors 24. A four-lead IPG 10 can also be used for Deep BrainStimulation (DBS) in another example. In other IPG examples designed forimplantation directly at a site requiring stimulation, the IPG can belead-less, having electrodes 16 instead appearing on the body of the IPGfor contacting the patient's tissue.

As shown in the cross section of FIG. 1B, the IPG 10 includes a printedcircuit board (PCB) 40. Electrically coupled to the PCB 40 are thebattery 36, which in this example is rechargeable; other circuitry 50 aand 50 b coupled to top and bottom surfaces of the PCB; a telemetry coil42 for wirelessly communicating with an external controller (not shown)using telemetry modulation/demodulation circuitry 43 (FIG. 2); acharging coil 44 for wirelessly receiving a magnetic charging field froman external charger 90 (FIG. 2) for recharging the battery 36; and thefeedthrough pins 34 (connection not shown). If battery 36 is permanentand not rechargeable, charging coil 44 would be unnecessary. (Furtherdetails concerning operation of the coils 42 and 44 and the externaldevices with which they communicate can be found in U.S. PatentApplication Ser. No. 61/877,871, filed Sep. 13, 2013).

Battery management circuitry 84 for the rechargeable battery 36 in theIPG 10 is described in one example in commonly-owned U.S. PatentApplication Publication 2013/0023943, which is incorporated herein byreference in its entirety, and shown in FIG. 2. Rechargeable battery 36may comprise a Li-ion polymer battery, which when fully charged canprovide a voltage (Vbat=Vmax) of about 4.2 Volts. However, otherrechargeable battery chemistries could be used for battery 36 as well.

An external charger 90, typically a hand-held, battery-powered device,produces a magnetic non-data modulated charging field 98 (e.g., 80 kHz)from a coil 92. The magnetic field 98 is met in the IPG 10 by front-endcharging circuitry 96, where it energizes the charging coil 44 byinducing a current in the coil. The induced current is processed byrectifier circuitry 46, including a rectifier and optionally a filteringcapacitor and a voltage-magnitude-limiting Zener diode, e.g., to 5.5V),to establish a voltage V1 (e.g., ≦5.5V), which voltage is passed througha back-flow-prevention diode 48 to produce a DC voltage, Vdc. LSKmodulation circuitry 45, including transistors 102 coupled to thecharging coil 44, can be controlled by the IPG 10 (via control signalLSK) to transmit data back to the external charger 90 during productionof the magnetic field 98 via Load Shift Keying, as is well known.

Vdc is provided to battery management circuitry 84, which may reside onan Application Specific Integrated Circuit (ASIC) along with othercircuitry necessary for IPG 10 operation, including current generationcircuitry (used to provide specified currents to selected ones of theelectrodes 16); telemetry circuitry 43; various measurement andgenerator circuits; system memory; etc. The front-end charging circuitry96 and the battery 36 typically comprise off-chip (off-ASIC) components,along with other electronics in the IPG 10, such as the telemetry coil42; various DC-blocking capacitors coupled to the electrodes 16 (notshown); a microcontroller 100, which can communicate with the ASIC (andthe battery management circuitry 84) via a digital bus 88; and othercomponents of lesser relevance here. Microcontroller 100 may comprise inone example Part Number MSP430, manufactured by Texas Instruments, whichis described in data sheets athttp://www.ti.com/lsds/ti/microcontroller/16-bit_msp430/overview.page?DCMP=MCU_other& HQS=msp430, which is incorporated herein by reference.The ASIC may be as described in U.S. Patent Application Publication2012/0095529, which is also incorporated herein by reference.

The battery management circuitry 84 in FIG. 2 is comprised of twocircuit blocks: charging circuitry 80 for generating a current forcharging the battery 36, and load isolation circuitry 82 forcontrollably connecting or disconnecting the battery 36 from the load 75that the battery 36 powers during normal operation of the IPG 10. Load75 can comprise both on-chip (on-ASIC) circuit blocks such as thecurrent generation circuitry and the telemetry circuitry 43 mentionedearlier, and off-chip (off-ASIC) components such as the microcontroller100.

As depicted, the charging circuitry 80, the load isolation circuitry 82,and the battery 36 generally have a T-shaped topology, with the chargingcircuitry 80 intervening between front-end charging circuitry 96 (Vdc)and the positive terminal (Vbat) of the battery 36, and with the loadisolation circuitry 82 intervening between Vbat and the load 75.

The load isolation circuitry 82 can prohibit the battery 36 (Vbat) frombeing passed to power the load (Vload) dependent on a number ofconditions. For example, if the load 75 is drawing a significantly highcurrent (as indicated by overcurrent detection circuitry 74 viaassertion of control signal OI), or if Vbat is too low (as indicated byundervoltage detection circuitry 70 via assertion of control signal UV),or if an external magnetic field signal μ is indicated by a Reed switch78 (e.g., in an emergency condition warranting presentation by thepatient of an external shut-off magnet), the load 75 will be decoupledfrom Vbat via switches 62 or 64, as assisted by OR gate 76. Dischargecircuitry 68 is also provided to intentionally drain the battery 36 ifVbat is too high.

Charging circuitry 80 begins at Vdc, where it splits into two pathsconnected in parallel between Vdc and Vbat: a trickle charging path, andan active charging path, either of which can be used to provide acharging current (Ibat) to the battery 36 (Vbat).

The trickle charging path is passive, i.e., its operation is notcontrolled by control signals, and requires no power other than thatprovided by Vdc to produce a charging current (Itrickle) for the battery36. As shown, the trickle charging path presents Vdc to acurrent-limiting resistor 50 and one or more diodes 52, and is used toprovide a small charging current, Itrickle, to the battery 36. Using asmall trickle charging current is particularly useful when the battery36 is significantly depleted, i.e., if Vbat is below a threshold Vt1,such as 2.7V for example. Itrickle is usually on the order of tenmilliamps.

The active charging path proceeds in FIG. 2 from Vdc to the battery 36through a current/voltage source 56, which is used to produce chargingcurrent Iactive. In the example of FIG. 2, the active charging path alsopasses through control and protective measures for the batterymanagement circuitry, including a charging current sense resistor 58used in conjunction with a charging current detector 72, and anovervoltage protection switch 60 used in conjunction with an overvoltagedetector 66 to open circuit the active charging path if the batteryvoltage, Vbat, exceeds a maximum value (such as Vmax=4.2V).

Circuitry for the current/voltage source 56 in the active charging pathis shown in FIG. 3A. As its name implies, source 56 can be controlled toprovide either a constant current or a constant voltage to the battery36 during active charging. The source 56 comprises a current mirrorcomprised of P-channel transistors 104 and 106, which is powered by Vdcand receives a reference current, Iref, provided by reference currentgenerator circuitry 113. Current mirror control transistor 104 mirrors ascaled (M) representation of Iref in current mirror output transistor(s)106 to produce the active charging current, Iactive=M*Iref.

The reference current generator circuitry 113 used to produce Iref isadjustable via control signals Itrim[2:0], which in turn are used toadjust Iactive. Control signals Itrim are issued by a source controller86, which receives instructions from the microcontroller 100 by adigital bus 88 (FIG. 2). The source controller 86 likewise issuescontrol signal Ch_en to enable/disable the reference current generatorcircuitry 113.

The mode in which the source 56 operates to generate a charging currentdepends on the magnitude of the battery voltage, Vbat, which is known tothe microcontroller 100. If the battery 36 is significantly depleted,i.e., Vbat<Vt1 (e.g., 2.7), the microcontroller 100 commands the sourcecontroller 86 to disable the source 56 (Ch_en=‘0’) to prevent it fromproducing Iactive. Thus, the battery 36 in this circumstance can only becharged via the trickle charging path, and only if magnetic field 98 andVdc are present and sufficient.

If Vbat>Vt1, but below an upper threshold Vt2 described further below(i.e., if Vt1<Vbat<Vt2), the source 56 operates in a constant currentmode. In this mode, the source 56 is enabled (Ch_en=‘1’), allowingIactive to flow in accordance with a value represented by the Itrimcontrol signals. When source 56 operates in constant current mode,Iactive is generally on the order of 50 milliamps.

If Vbat>Vt2 (e.g., 4.0 V), the source 56 operates in a constant voltagemode. Crossing of the Vt2 threshold and switching of charging modes isaffected via Vbat measurement circuitry 111, which controls amplifier112 to start turning off transistor 114 in the active charging path. Thevalue of Vt2 is set by the Vtrim control signals. Once in constantvoltage charging mode, Iactive thus begins to fall off exponentially,until Vbat reaches a maximum value, Vmax (e.g., 4.2V), at which pointthe microcontroller 100 will consider charging of the battery 36 to becomplete. FIG. 3B generally illustrates operation of the chargingcircuitry 80 to produce the charging current (Ibat) received by thebattery 36 as a function of time during a charging session, includingthe trickle, constant current, and constant voltage modes.

The battery management circuitry 84 of FIG. 2 provides additionalsafeguards, such as diode(s) 54 connected between the trickle and activecharging paths to prevent leakage of the battery 36 through theovervoltage switch 60.

Referring again to FIG. 2, the microcontroller 100 in the IPG 10includes an shutdown register 115, in which is stored a future time ortime interval from beginning of use of the IPG 10 (tSD) at which the IPGwill cease therapeutic operations (although non-therapeutic operationssuch as telemetry may still function if possible), and will thus nolonger provide stimulation therapy to the patient. tSD in the shutdownregister 115 is typically set by the IPG manufacturer, and may comprise12 years in one example. Once tSD is reached, the IPG 10 will need to beexplanted from the patient, and a new IPG implanted. tSD may bepopulated in the IPG, or the 12-year time interval may start running,under manufacturer or implanting clinician control for example.

tSD serves important purposes. First, tSD may represent a time afterwhich the manufacturer believes the IPG 10 might fail or begin workingunreliably or unsafely, perhaps as determined via reliability testing atthe manufacturer. Second, tSD sets a date after which the manufacturer'sresponsibility or liability for the IPG 10 is limited or suspended. Forexample, the manufacturer may provide a warranty and support regardingthe IPG 10 and supporting external components which expires once tSD haspassed. Thus, tSD provides certainty to the manufacturer as to itsobligations vis-à-vis the IPG and the patient.

Third, tSD is used to warn the patient or clinician in advance that IPG10 operation will soon be suspended. In this regard, the IPG 10determines an early replacement indicator from tSD, which may be timedto occur (tSDi) at a set time period (tGRACE) before tSD occurs (i.e.,tSDi=tSD−tGRACE). tSDi may be stored in its own register 117 as shown.When tSDi arrives, an indication is provided to a patient or clinicianexternal device via telemetry from the IPG 10 using telemetry coil 42and its associated telemetry circuitry 43. The IPG 10 may attempt toinitiate such communications, or the IPG 10 may hold the tSDi indicationin a manner flagging it as priority data to be sent to the externaldevice once the external device initiates a communication session withthe IPG 10. Once communicated to the external device, the tSDiindication can for example be viewed on a display of the externaldevice, informing the patient that IPG operation will soon be suspended,and perhaps also informing the patient of the particular date or timethat tSD will occur. This early warning allows the patient to plan tocontact his clinician or the manufacturer to discuss explanation of theIPG 10, and replacement with a fresh IPG.

However, the inventors consider it unfortunate that tSD (and byextension, its earlier indicator tSDi) comprises a fixed time period setby the manufacture at the outset of use of the device. The inventorsrecognize that in reality the time at which IPG 10 would reach its endof its life will be determined at least in part by how strenuously theIPG 10 is used by each patient. For example, if an IPG providesrelatively low stimulation therapy to a patient, that patient's IPG maystill be perfectly functional and safe even after tSD has passed. Such apatient might wish to continue to use the IPG 10 after this time (evenif not warranted or supported by the manufacturer) to delay explantationsurgery as long as possible. Moreover, the manufacturer may be willingto extend warranty and support to such a patient for at least someperiod beyond tSD. On the other hand, another patient requiring morestrenuous stimulation therapy may exhaust the life of his IPG before tSDexpires. This presents a problem for both the patient and themanufacturer: the patient may be upset regarding the IPG's performance,having expected it to last at least until tSD, and must undergoexplantation earlier than expected; and the manufacturer may need tocontinue to warrant and support the IPG, even though the IPG was notfaulty, but was nonetheless used (perhaps unusually) strenuously.

SUMMARY

Circuitry for a medical device is disclosed, comprising: a rechargeablebattery; control circuitry configured to configured to implement analgorithm, wherein the algorithm is configured to: estimate a firstcapacity of the battery, and forecast and/or determine an end of life ofthe medical device using at least the estimated first capacity of thebattery.

The algorithm may be further configured to store previously-estimatedbattery capacities, and the algorithm may forecast and/or determine theend of life using the estimated first capacity and the previouslyestimated capacities. The first and previously estimated batterycapacities may each be associated with a time, and wherein the algorithmforecasts and/or determines and end of life by deriving a function ofbattery capacity versus time.

The algorithm forecasts and/or determines the end of life in accordancewith a first capacity threshold, and may be configured to forecastand/or determine an early indicator of the end of life. The earlyindicator may comprises a set time before the forecasted end of life, orthe algorithm may forecast and/or determine the early indicator inaccordance with a second capacity threshold. The algorithm may befurther configured to store the forecasted and/or determined earlyindicator for transmission to an external device.

The algorithm may suspend therapeutic operation of the medical devicewhen the end of life is determined, or may use the forecasted end oflife to extend therapeutic operation of the medical device beyond ashutdown time.

The control circuitry may further comprises a memory configured to storeat least one parameter having an effect on a capacity of therechargeable battery, wherein the at least one parameter is selectedfrom a group consisting of one or more parameters relevant to: previouscharging of the battery, previous use of the medical device to providetherapy, and the age of the battery; in which the algorithm isconfigured to estimate the first capacity of the battery using the atleast one parameter. The at least one parameter may be stored as afunction of time in the memory, or stored as a present value for use bythe algorithm. The at least one parameter may also comprises a valuecomputed from at least one other parameter measured during previouscharging of the battery or previous use of the medical device.

Parameters relevant to previous charging of the rechargeable battery maycomprise a number of previous charging session, a voltage of the batteryat the start of a previous charging session, a voltage of the battery atthe end of a previous charging session, a duration of a previouscharging session, a charge provided to the battery during a previouscharging session, a discharge depth comprising a difference between avoltage of the battery at the start and finish of a previous chargingsession, and a battery charging current provided to the battery during aprevious charging session.

Parameters relevant to previous use of the medical device to providetherapy may comprise a voltage of the rechargeable battery during aprevious use, a load current drawn from the battery during a previoususe, a power drawn from the battery during a previous use, a duration ause, and a charge drawn from the battery during a previous use.

The circuitry may further comprises a battery capacity database, inwhich the battery capacity database associates the at least oneparameter with a change in the capacity of the battery, wherein thealgorithm compares the at least one parameter to a change in thecapacity in the battery capacity database to determine the firstcapacity of the battery. The memory may further comprises a weight orpriority of each at least one parameter, in which the algorithm isconfigured to determine the first capacity of the battery by using theweigh or priority or both the weight and priority of the at least oneparameter.

Also disclosed is a method for operating a medical device having arechargeable battery, comprising: estimating a first capacity of therechargeable battery, and forecasting and/or determining an end of lifeof the medical device using at least the estimated first capacity of thebattery. The disclosed method may use aspects of the circuitry asdescribed above.

Further circuitry for a medical device is also disclosed, comprising: arechargeable battery; a first register configured to store a shutdowntime at which therapeutic operation of the medical device will besuspended; control circuitry configured to configured to implement analgorithm, wherein the algorithm is configured to: determine an end oflife of the medical device using at least a first estimated capacity ofthe battery; and suspend therapeutic operation of the medical deviceeven if the shutdown time has not been reached. The algorithm may befurther configured to resume therapeutic operation of the medical deviceupon receipt of an override. The algorithm may be further configured toforecast an end of life of the medical device using at least a secondestimated capacity of the battery; determine that the shutdown time hasbeen reached; continue therapeutic operation of the medical device ifthe forecasted end of life is greater than the shutdown time; andsuspend therapeutic operation of the medical device if the determinedend of life is not greater than the shutdown time. The algorithm may beconfigured to continue therapeutic operation of the medical device byadjusting the shutdown time to a later time in the first register, whichlater time may be between the shutdown time and the forecasted end oflife or which may be of a fixed duration.

Further circuitry for a medical device is also disclosed, comprising: arechargeable battery; a first register configured to store a shutdowntime at which therapeutic operation of the medical device will besuspended; control circuitry configured to configured to implement analgorithm, in which the algorithm is configured to: forecast an end oflife of the medical device using at least a first estimated capacity ofthe battery; determine that the shutdown time has been reached; continuetherapeutic operation of the medical device if the forecasted end oflife is greater than the shutdown time; and suspend therapeuticoperation of the medical device if the determined end of life is notgreater than the shutdown time. The algorithm may be configured tocontinue therapeutic operation of the medical device by adjusting theshutdown time to a later time in the first register, which later timemay be between the shutdown time and the forecasted end of life, orwhich may be of a fixed duration.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B show an implantable pulse generator (IPG) with arechargeable battery in plan and cross sectional views, in accordancewith the prior art.

FIG. 2 shows battery management circuitry for the rechargeable batteryIPG including both trickle and active charging paths, in accordance withthe prior art.

FIG. 3A shows circuitry for a current/voltage source in the activecurrent path, while FIG. 3B shows a graph of the battery chargingcurrent provided by both the trickle and active charging paths as afunction of time, in accordance with the prior art.

FIG. 4 shows improved circuitry for a rechargeable battery IPG includingan algorithm used to forecast and determine tEOLi and tEOL in accordancewith logged historical parameters relevant to rechargeable batterycapacity, in accordance with an aspect of the invention.

FIG. 5A shows a capacity-relevant parameter log, FIG. 5B shows presentcapacity-relevant parameters determined from the log, and FIG. 5C showsa battery capacity database, which are used in accordance with the EOLalgorithm, in accordance with an aspect of the invention.

FIGS. 6A-6E show initial operation of the EOL algorithm, in accordancewith an aspect of the invention.

FIG. 7 shows later operation of the EOL algorithm, in accordance with anaspect of the invention.

FIG. 8 shows a shutdown algorithm useable in conjunction with tEOL andtSD to determine when to suspend IPG therapeutic operation.

DETAILED DESCRIPTION

Many events can occur which could cause an Implantable Medical Device(IMD) such as an IPG to reach its end of life at a time tEOL. Thecircuitry could fail, either as a result of defects, or because thecircuitry has simply worn out and is no longer operating in accordancewith its specifications. Mechanical defects or wear out can also causethe IMD to fail, such as a breech in the IMD's hermetic case 30,mechanical damage to the electrical components in the case 30 and in theheader 28, etc.

Additionally, the end of life of an IMD may result from wear out of itsrechargeable battery. The inventors consider rechargeable battery wearout to be a predominant factor in determining the life of a rechargeablebattery IMD. Battery wear out—more specifically loss of batterycapacity—may be of greater significance than other electrical ormechanical failure modes. Although random electrical and mechanicaldefects can occur in an IMD, circuitry and mechanics in the IMD shouldotherwise last a lifetime before they are worn. Loss of battery capacityby contrast will occur in any rechargeable-battery IMD, and such wearingof the battery will often cause the IMD to stop working satisfactorilylong before electrical or mechanical wear out would do so.

The inventors are aware that certain parameters can affect the capacityof the rechargeable battery over the lifetime of an IMD, includingbattery calendar age (A), and various parameters pertaining to stressesimparted to the rechargeable battery. Such parameters can relate tobattery charging, such as the number of times the battery has beenrecharged (Nc); the charging current used to recharge the battery(Ibat); how long it takes to recharge the battery (Tc), which inconjunction with the charging current determines the total charge (Cc)the battery has received (Cc=Ibat*Tc); and the discharge depthindicating the difference in the battery voltage from the start to thefinish of a charging session (ΔVbat). Such parameters can also relate touse of the battery to provide power to the IMD, such as the current(Iload) or charge (Cu=Iload*Tu, where Tu equals the time of use) drawnfrom the battery by the load 75 during regular operational periods inwhich battery charging may not be occurring.

These parameters tend to reduce the capacity of the battery over time asthey contribute to chemical and physical changes in the rechargeablebattery. As battery capacity decreases over time, the rechargeablebattery will eventually wear to a point where it can no longer becharged to operate the IMD for a significant time. In this regard,considering when the rechargeable battery has reached its end of lifemay be subject to interpretation. For example, if it takes an hour torecharge the battery, which then enables the IMD to provide therapy foronly an hour, most would consider the rechargeable battery to havereached the end of its life as a practical matter, even thoughtechnically the battery can still be used and hasn't suffered acatastrophic failure. In short, the end of life of a rechargeablebattery (at time tEOL) is largely a qualitative judgment. While theshutdown time tSD used in the prior art may desire to approximate thetEOL, the two are not the same, as tSD does not consider actual stressesthat rechargeable battery will endure during use, which can vary frompatient to patient. As implied in the Background, tEOL for a light-useIMD patient may be well beyond tSD, and tEOL for a strenuous-use IMDpatient may be well before tSD. In neither case does tSD comprise anactual quantitative determination that the rechargeable battery IMD hasactually reached its end of life, but is instead, at best, a statisticalvalue derived from reliability testing, which as just noted may not fitall realistic IPG use situations.

The inability of the prior art to quantitatively determine tEOL for arechargeable battery IMD is problematic because a rechargeable batteryof reduced capacity will be more easily depleted to unsuitably lowlevels, or will do so more quickly that when the battery 36 was new. IfVbat is severely depleted, i.e., if Vbat<2.0V for example, it may bedifficult to recover (recharge) the battery 36. This is explained infurther detail in the above-referenced 61/928,342 application, which maybe used in conjunction with the disclosed technique. In short, without aquantitative measure of tEOL, the risk of such battery depletion isincreased. This is particularly true for strenuous-use IMD patients, whoare otherwise permitted by the prior art to use their implants prior tothe expiration of tSD, when in reality they have exhausted their IMDsand should have them explanted.

In contrast to rechargeable battery IMDs, tEOL of a non-rechargeablebattery IMD is easier to determine, and can simply comprise a batteryvoltage threshold, e.g., Vbat(EOL), below which the non-rechargeablebattery can no longer reliably operate the circuitry in the IMD.Moreover, tEOL can also be more easily forecasted for a non-rechargeablebattery IMD. For example, the IMD can track Vbat as it decreases overits life, and can extrapolate as to when Vbat is likely to reachVbat(EOL), thus providing a quantitative means of forecasting tEOL.Moreover, the ability to easily quantify tEOL in non-rechargeable IMDsallows for warning the patient in advance that tEOL is impending, suchas by the issuance of an early replacement indicator (EOLi), similar tothe manner in which advanced notice of shutdown at tSD is provided tothe rechargeable battery IMD patient by tSDi. The time at which tEOLimay issue for a non-rechargeable battery IPG can, like tSDi, be set inaccordance with fixed a grace period referenced to tEOL (i.e.,tEOLi=tEOL−tGRACE), or may also occur when the battery voltage passes athreshold Vbat(EOLi) that is slightly higher than Vbat(EOL). See, e.g.,U.S. Patent Application Ser. No. 61/887,231, filed Oct. 24, 2013. Ofcourse, forecasting tEOL using Vbat as a function of time is notpossible in a rechargeable battery IMD: Vbat does not continuallydecrease over the life of a rechargeable battery IMD, but insteadoscillates as the battery is continually used and recharged.

The inventors have determined that it is desirable to quantitativelydetermine when tEOLi and tEOL have been reached for a rechargeablebattery in an IMD, and similarly to quantitatively forecast when tEOLiand tEOL might issue in the future. These determinations and forecastsfor tEOLi and tEOL occur in accordance with one or more of thecapacity-relevant parameters noted above, including parameters relevantto battery charging (e.g., Nc; Ibat; Tc; Cc; ΔVbat), battery use (e.g.,Iload), and/or battery age (A). Specifically, an algorithm operable inthe IMD consults such parameters as stored over the history of theoperation of the IMD in a parameter log, and determines and forecaststEOLi and tEOL accordingly, as will be explained below.

Quantitatively determining and forecasting tEOLi and tEOL is significantin the context of a rechargeable battery IMD, and to the inventors'knowledge is novel. Unlike the prior art discussed earlier in which tSDiand tSD for a rechargeable battery IMD are merely predetermined by themanufacturer at the outset of the IPG's life, the disclosed techniqueinstead considers parameters in the IMD reflective of the stresses onthe rechargeable battery's capacity, which as noted earlier can drivetEOL, and hence its associated tEOLi. Such parameters can for exampledistinguish light or strenuous use of the rechargeable battery in theIMD, which as noted above can vary from patient to patient, thusallowing tEOLi and tEOL to be determined or forecasted for each IMD andeach patient based on such use. Thus, light use of the IMD by aparticular patient will result in an increased values for tEOLi andtEOL, while heavy use by a particular patient will result in a decreasedvalues for tEOLi and tEOL.

In short, the disclosed technique provides a quantitative and realisticway of determining and forecasting the end of life of the rechargeablebattery IMD, aiding both the patient and the manufacturer. Themanufacturer may for example sell the IMD with conditional warranty andsupport obligations contingent on tEOL as forecasted or determined.Thus, the manufacturer's obligation to a strenuous-use IMD patient mayexpire or be limited more quickly than traditional preset times (e.g.,tSD) would warrant (e.g., <12 years). Conversely, the manufacturer mayallow a light-use patient to continue operating her IMD beyond tSD,and/or may allow its warranty and support obligations to be extendedbeyond tSD if tEOL for a light-use IMD patient is determined or isforecasted to occur later (e.g., >12 years). Thus, the IMD may notsimply stop operating upon expiration of tSD, as discussed furtherbelow.

FIG. 4 shows improved circuitry for an implantable medical device suchas an IMD 10 having a rechargeable battery 36 which allows for tEOLi andtEOL determination and forecasting. Many of the components are unchangedfrom the prior art as shown in FIG. 2, and are thus not described againfor simplicity.

The microcontroller 100 has been programmed to implement an EOLalgorithm 160. Input to the algorithm 160 are two data sets: acapacity-relevant parameter log 120, and a battery capacity database122, which are shown in detail in FIGS. 5A-5C. Stated simply, thecapacity-relevant parameter log 120 contains historical parameters suchas those discussed above that have an impact on battery capacity,including data regarding past charging and use of the IMD 10 and itsage. The battery capacity database 122 comprises data correlating theparameters to battery capacity. This database 122 is preferablyprogrammed by the manufacturer based on its understanding of therelevance of the parameters to the particular rechargeable battery 36 athand.

Thus, the EOL algorithm 160 reviews historical parameters relevant tobattery capacity in the log 120, and reviews such parameters in light ofthe correlations in the database 122, to determine and forecast tEOLiand tEOL. As shown, additional registers 124 and 126 are provided tostore tEOLi and tEOL as forecasted or determined. Indicator bits 125 and127, which may be associated with the registers 124 and 126, cancomprise single bits indicating whether tEOLi and tEOL have already beendetermined—that is, if these times have already been reached.

The shutdown register 115, including its present shutdown time tSD, canalso be provided in the IPG 10, as occurred in the prior art. However,as discussed further below, while tSD can still operate to shut downoperation of the IMD 10, it doesn't necessarily do so, or it can beadjusted to be commensurate with tEOL as forecasted.

One example of the capacity-relevant parameter log 120 is shown in FIG.5A. Note that some or all of the data in the log 120 may already bestored during normal operation of the IMD 10, and thus log 120 merelyshows the collection of such data in a convenient form. For ease ofviewing, the capacity-relevant parameter log 120 has been split intothree sections 120 c, 120 u, and 120 a.

Section 120 c contains historical parameters procured or computed duringprevious charging sessions, including the number of the charging session(Nc); the voltages of the battery 36 at the start and finish of thecharging session (Vbat(i), Vbat(f)), from which the discharge depth(ΔVbat) can be computed; and the charging current, Ibat. Note that Ibatpreferably comprises a measurement of the actual current provided by thesource 56 in the active charging path, as opposed to the Iactive valueto which the source 56 was programmed (by the Itrim control signals).This is preferable, because programming the source 56 (FIG. 2) toprovide a particular Iactive does not guarantee that such current wasactually provided to the battery 36. This is particularly true if thecoupling between the external charger 90 and the IMD 10 is poor,providing a Vdc to the source 56 that is too low to produce theprogrammed current. The actual Ibat in the log 120 may be measured usingby sensing a voltage drop across charging current sense resistor 58using charging current detector 72, which produces an analog signal CIthat can be digitized (FIG. 2).

Note that Ibat in the capacity-relevant parameter log 120 contains nodata concerning the trickle charging path (Itrickle) during the relevantcharging session. As Itrickle is generally low compared to Iactive, itscontribution as a parameter relevant to battery capacity and hencetEOLi/tEOL may be insignificant, and thus ignored. This is fortunate,because Itrickle may be difficult to accurately measure, as Vbat is low,and the IMD 10 circuitry thus unreliable, when significant tricklecharging is occurring.

Also shown in section 120 c is the duration of the charging session(Tc). This may be determined using the IMD's internal clock, asreflected in the timestamp values that are optionally provided in thelog 120. From the charging time Tc, a total charge (Cc) provided to thebattery during the charging session may be computed (Ibat*Tc).

Section 120 u shows parameters relevant to battery capacity duringregular use of the IMD 10, for example, to provide therapy to thepatient. As noted above, the power drawn by the IMD 10 (e.g., Iload)affects battery capacity, and so Iload is included in 120 u. Althoughnot shown, the battery voltage Vbat could also be provided in 120 u,which would provide a truer indication of power draw (P=I*V), which mayalso be included as a parameter in 120 u. Use durations (Tu) are alsoprovided, from which a total charge (Cu) can be determined (Iload*Tu).Note that Iload is a dynamic parameter when the IMD 10 operates, andwill be significantly higher during those time periods when the IMD 10is actually providing pulses to the electrodes 16. As such, thefrequency, duration, and intensity of such pulses will affect (orlargely determine) Iload and Cu, which may represent a scaled or averagevalue. See, e.g., U.S. Patent Application Ser. No. 61/873,314, filedSep. 3, 2013. Iload can also be measured directly, using the techniquedisclosed in U.S. Patent Application Ser. No. 61/891,730, filed Oct. 16,2013. Although the timestamps in sections 120 c and 120 u suggest forsimplicity that charging and use do not overlap in time (note theinterleaved timestamps, tx), this is not strictly necessary, as the IMD10 can generally continue to be used during a charging session.

Section 120 a merely shows the IMD's age, as reflected by the currenttimestamp. Note that the some of the parameters in log 120 thatoriginate in battery management circuitry 84 (e.g., Ibat, Iload) can becommunicated to the microprocessor 100 via the bus 88 for storage in thelog 120.

The particular structure of capacity-relevant parameter log 120 canvary, and need not comprise a unified single structure or file used bythe EOL algorithm 160. Particularly if some of the parameters arealready logged in the IMD 10 for some other reason, the parameters mayreside in different data structures in the IMD, which are simply queriedby the algorithm 160. The algorithm 160 may additional include theability to compute relevant parameters (e.g., charge Cc, which equalsIbat*Tc), and so the log 120 need not pre-compute such values for thealgorithm 160's convenience.

Note that the illustrated parameters comprising log 120 are subject tomanufacturer preferences, and perhaps even manufacturer experience withthe wear out of the particular rechargeable battery 36 used in the IMD.Thus, a manufacturer may consider some of the parameters illustrated inFIG. 5A to be irrelevant (or of only minor relevance) to batterycapacity, and so may not be included in the log 120. Anothermanufacturer may consider additional parameters not shown to be morerelevant to battery capacity, and so may include such additionalparameters. In short, the parameters included in the capacity-relevantparameter log 120 as illustrated in FIG. 5A should be understood as onlyone example of the parameters useful for tEOLi and tEOL forecasting anddetermination.

As discussed in detail later, the EOL algorithm 160 will consult theparameters in the log 120 to adjust tEOLi and tEOL from time to time.FIG. 5B shows a manner in which the data in the log 120 may besummarized for easier use by the algorithm 160 in the form of presentcapacity-relevant parameters 120′, which summarizes the parameters foruse by the algorithm at the present time. For example, the total chargeimparted to the battery 36 during charging over the life of the IMD,Cc(tot), is provided, which comprises a sum of the charge values Cc fromsection 120 c of the log 120. As shown in FIG. 5B, this summed charge iscurrently represented by value Cc(tot)2, which would grow over time. Thetotal charge expended during use of the IMD, Cu(tot) is similarlyprovided, which is currently represented by value Cu(tot)2. Alsoprovided in present parameters 120′ is the total number of times the IMDhas been charged, Nc, as represented currently by Nc4, which wouldcomprise the last value for Nc in section 120 c of the log 120. Averagedischarge depth, ΔVbat(avg), and average charging and use currents,Ibat(avg) and Iload(avg), are also provided by averaging the individualvalues in section 120 c.

Present capacity-relevant parameter Z in log 120′ comprises a ratio ofthe charge expended during use (Cu(tot)) and the charge imparted to thebattery during charging (Cc(tot)). This parameter is relevant, andshould ideally equal one, because the charge input to the battery andoutput from the battery should theoretically be the same absent aproblem. Of course, the accuracy of this ratio depends on how accuratelythe total charges can be calculated. Nonetheless, a baseline value of Zfor a properly operating IMD 10 with good battery capacity can still beestablished even if the total charges are imperfectly measured. If thevalue for Z decreases over time, this suggests that an increasing amountof charge imparted to the battery during charging is not being used bythe circuitry in the IMD, and hence that a battery capacity problem mayexist such as leakage in the rechargeable battery 36.

Just as the parameters included in the log 120 are subject tomanufacturer preferences and experiences, so too is the data included inpresent parameter log 120′, and the manner in which such data isdigested from the log 120. To cite some simple examples, themanufacturer may consider small discharge depths (ΔVbat) to beirrelevant to battery capacity and operation of the EOL algorithm 160,and so may exclude values smaller than a threshold from the average in120′. Or, the manufacturer may wish to include as a present parameter in120′ the percentage of the time that the discharge depth hashistorically been above this threshold.

Present parameters 120′ may also not necessarily reflect data occurringover the entire history of the log. For example, Ibat(avg), Iload(avg),and ratio Z may be more relevant when determined from more-recent datain the log 120, and thus may be computed using only data in the logoccurring over a recent time period, such as one month. Using only arecent portion of the log 120 may be particularly useful if changes tothe operation of the IMD 10 are made that would impact battery capacity.For example, in the above-referenced 61/928,352 application, which maybe used in conjunction with the disclosed technique, it is taught thatthe charging current Ibat can be adjusted (e.g., reduced) over time todecrease the rate at which the battery capacity is decreasing. Shouldthis occur, it may be warranted to assess only capacity-relevantparameters in the log 120 that have occurred since such adjustment sothat the tEOLi and tEOL forecasts and determinations are not skewed byold data that is no longer representative of the current stresses on theIMD and rechargeable battery 36.

The parameters illustrated in FIG. 5B provide merely one example usefulto illustrating the disclosed technique. Present capacity-relevantparameters 120′ may comprise a portion of the log 120, or be separate.Also, the present capacity-relevant parameters 120′ may be automaticallyupdated pursuant to a schedule, or computed or updated once the EOLalgorithm 160 runs.

An example of the battery capacity database 122 is shown in FIG. 5C. Asnoted earlier, the battery capacity database 122 comprises datacorrelating the parameters in the log 120 (or preferably the parametersas digested in log 120′) to battery capacity. As shown, the database 122depicts how particular values for the parameters affects batterycapacity. For example, if the total charge provided to the batteryduring charging comprises a value of Cc(tot)2 (or a value betweenCc(tot)2 and Cc(tot)3), database 122 reflects that battery capacity isreduced by 2%. Note that the effect of battery capacity could also bereflected in database 122 using values other than percentages, althoughpercentages are used herein for easy illustration.

As noted, the data in database 122 is preferably determined by the IMDor battery manufacturer based on their understanding of the effect ofeach of the parameters on battery capacity. For example, in determiningan appropriate percentage adjustment for parameter Cc(tot), themanufacturer may experimentally determine or measure the batterycapacity once Cc(tot)1, Cc(tot)2, etc. have been reached, and set thepercentages in the database 122 accordingly.

As shown for simplicity in FIG. 5C, the relationship between theparameter values and the percentages in FIG. 5C are reflective of theeffect of just that parameter on battery capacity, absent considerationof other parameters. Alternatively, although not shown, more complicatedmulti-parameter relationships may be reflected. For example, database122 may reflect a percentage dependent on two or more parameters: e.g.,if Cc(tot)>A, but Iload(avg)<B, then the percentage is C %; or ifΔVbat(avg)*Ibat(avg)=P(avg)>X, then the percentage is Y, etc.

Note that most of the parameters in battery capacity database 122reflect that battery capacity decreases (hence the negative percentages)as the values for the parameters increase. However, this is not alwaysthe case, such as for ratio Z discussed above. Moreover, while all ofthe parameters are shown to result in a reduction of battery capacity,this might not always be the case, as some parameters (particularly ifdifferent battery chemistries are used, or given how the variousparameters are mathematically processed) might result in an increasedcapacity over time (a positive percentage).

Battery capacity database 122 additionally may include data regardingthe weight of the parameters, or a priority in which such parametersshould be applied by the EOL algorithm 160 when determining orforecasting tEOLi and tEOL. For example, it is seen that themanufacturer considers total charge during charging (Cc(tot)) to be theparameter having the most significant impact on battery capacity. Thus,this parameter is provided a weight of ‘1’ (suggesting it will be fullyconsidered by the algorithm 160 without scaling), and is accorded thehighest priority. By contrast, the average discharge depth (ΔVbat(avg))is deemed to be less significant, and thus carries a weight of 0.5 andis fourth highest in priority. Again, these weights and priorities indatabase 122 are subject to manufacturer preferences and experience.

FIG. 6A illustrates the EOL algorithm 160 in one example. This portionof the algorithm 160 is used initially, before tEOLi (and hence tEOL,which occurs later) is determined. That is, tEOLi has not yet beenreached, and EOLi indicator bit 125 (and hence EOL indicator bit 127)has not yet been set in a previous run of the algorithm 160. Thus, theportion of algorithm 160 illustrated in FIG. 6A seeks to forecast (orupdate the forecast of) tEOLi and tEOL, and to assess whether tEOLi hasbeen determined and thus that EOLi indication bit 125 can be set. FIG.7, discussed later, illustrates later operation of the EOL algorithm 160once tEOLi has been determined (indicator bit 125 set), but tEOL hasnot. Thus, the portion of algorithm 160 illustrated in FIG. 7 seeks toforecast (or update the forecast of) tEOL, and to assess whether tEOLhas been determined and thus that EOL indication bit 127 can be set.After both tEOLi and tEOL have been determined (both indicator bits 125and 127 have been set), there is no further need to run algorithm 160,and thus the microcontroller 100 will preferably suspend operation ofthe algorithm 160 in any form at that time. Note that the EOL algorithm160 in FIGS. 6A and 7 do not consider the preset shutdown time (tSD) orits early indicator (tSDi) that may still be included in the IMD 10 (inregisters 115 and 117; FIG. 4). Discussion of the relevance of use ofthe shutdown time tSD in the context of the IMD is discussed withreference to shutdown algorithm 170 of FIG. 8.

As shown, the EOL algorithm 160 can be designed to run automatically ona schedule, with a periodicity long enough to gather a significantamount of new capacity-relevant parameter data in the log 120/120′, suchas every two weeks. This is not strictly necessary however, andalgorithm 160 could run on command (such as wirelessly received from anexternal device), or automatically upon the occurrence of certain eventsin the IMD 10 (completion of a charging session, certain failure modes,etc.).

The values for the present capacity-relevant parameters 120′ are queriedby the algorithm 160, which the algorithm may determine from log 120 atthis point if not determined and stored in advance. Then, percentchanges in battery capacity warranted for each of these values aredetermined using battery capacity database 122, as explained earlier.Actual values for the percent changes are provided in FIG. 6A to easeunderstanding of subsequent processing. Additionally, the weights andpriorities for each of the parameters may also be retrieved from thedatabase 122 if present.

At this point, the algorithm 160 will determine a total percent changein battery capacity, and processing of the data to determine this totalcan occur in several different ways, some of which are shown in FIG. 6B.For example, the algorithm 160 may just use the largest percentagechange (−7%) on the basis that this capacity-relevant parameter ishaving the largest effect on battery capacity. Alternatively, thealgorithm 160 may add (−28%) or average (−3.5%) the determinedpercentages, so that the effect of each parameter is considered to someextent.

Alternatively, the algorithm 160 may consider only a certain number(e.g., X=3) of the highest determined percentages (−7, −6, −5%), anddiscard all other lower percentages from subsequent analysis as beingtoo minimal in their effect on battery capacity. These remainingpercentages can then be added (−18%) or averaged (−6%) as before.Alternatively, these remaining percentages can be weighted using theretrieved weights (if present), and added (−9.2%).

Alternatively, the algorithm 160 may consider only a certain number(e.g., X=3) of the determined percentages (−2, −7, −5%) having thehighest priorities (1, 2, and 3), if such data is present. Thesepercentages may then be added (−14%), averaged (−4.7%), or weighted andadded (−10.6%) as described in the preceding paragraph.

In yet another example, the algorithm 160 may weight all of thedetermined percentages, if such weight data is present. These resultingweighted percentages may be then be added (−14.1%). This may comprise amost preferred manner of processing the percentages, as all areconsidered, with capacity-relevant parameters of lesser relevance havinga smaller effect on the total percent change. Alternatively, only themost relevant of the weighted percentages may be further considered(−5.6, −3, −2%) and added (−10.6%).

All of these alternatives for processing the determined percentages toarrive at a total percentage change indicative of the overall change inbattery capacity have some reasonable basis. Still other ways ofprocessing the capacity-relevant parameters are possible, depending onmanufacturer preferences and experience.

The total percentage comprises (or at least correlates to) an estimationof the battery capacity, which can be stored in an estimated capacitylog 162 (FIG. 4) associated with the EOL algorithm 160 along with atimestamp tx denoting when the estimation occurred, as shown in FIG. 6C.Note the previously-estimated battery capacities and their timestampsare also included in the log 162. In short, estimated capacity log 162records the battery capacity as estimated by the algorithm 160 as afunction of time.

In a next step of the EOL algorithm 160, a forecasting/determinationalgorithm 164 (FIG. 4) is run, which preferably (but not necessarily)uses the estimated capacity log 162 as its input. The algorithm 164 maycurve fit the entries in the estimated capacity log 162 (e.g., using aleast squares analysis) to extrapolate estimated battery capacity as afunction of time. As shown in FIG. 4, the algorithm 164 can also receiveas inputs thresholds to assist in the analysis of the estimated batterycapacities, such as a threshold capacity, Cap(th), which is used toforecast (and ultimately) determine tEOL, and tGRACE, which represents agrace period prior to tEOL at which the early replacement indicator isdetermined (tEOLi), as discussed further below.

Operation of the forecasting/determination algorithm 164 and therelevance of these thresholds are illustrated graphically in FIG. 6D.Shown are the estimated battery capacities as a function of time (e.g.,from log 162) for two patients A and B. As discussed, these data pointscan be curve fit, and the point at which the extrapolated curves crossCap(th) forecasts tEOL for the two patients (tEOL(A), tEOL(B)). Onceforecasted, tEOL can be stored for the respective patients in their EOLregisters 126. tGRACE can represent a fixed time period, such as sixmonths, before the forecasted issuance of tEOL, so a forecasted tEOLi(i.e., tEOLi=tEOL−tGRACE) can be also be stored in EOLi registers 124for both patients. As shown, patient A comprises a strenuous-use IMDpatient, and thus his forecasted values for tEOLi and tEOL are smallerthan light-use IMD patient B.

tEOLi can be forecasted in other manners, and independently of tEOL. Forexample, as shown in FIG. 6E, forecasting/determination algorithm 164forecasts and determines tEOLi using its own capacity threshold,Cap(th)(EOLi), different from the higher threshold, Cap(th)(EOL), usedto forecast and determine tEOL. Note that this alternative algorithm 164results in forecasts for tEOLi and tEOL that may not be spaced at afixed interval, as FIG. 6E shows.

Threshold Cap(th) (FIG. 6D), or thresholds Cap(th)(EOLi) andCap(th)(EOL) (FIG. 6E), are preferably programmed into the IMD 10 aspart of the EOL algorithm 160 by the manufacturer, with suchthreshold(s) being set based on manufacturer preferences and experience.As shown in FIG. 6D, the EOL threshold has been set to −60%, meaning thepoint at which the rechargeable battery 36 has lost 60% of its capacity.In FIG. 6E, the EOLi threshold is slightly lower, about −56%. Like theestimated capacities in log 162 themselves, these capacity thresholdsmay not exactly equal the actual battery capacity, but will nonethelesscorrelate to the actual battery capacity, and thus can be empiricallyset at a point where rechargeable battery performance is no longersufficient for reasonable operation—e.g., when the time needed torecharge the battery starts to rival the time that the IMD is used toprovide therapy. Note that Cap(th) and Cap(th)(EOL) may be setconservatively to assure that a small amount of capacity remains in casethe IMD needs power, for example, to provide telemetry even if thebattery capacity is too low for the IPG to provide therapy.

It is not strictly necessary that the forecasting/determinationalgorithm 164 use the estimated capacity log 162 to forecast ordetermine tEOLi or tEOL, and in fact it is not necessary thatpreviously-estimated battery capacities be stored in association withthe EOL algorithm 160 at all, although this is preferable andconvenient. Instead, algorithm 164 can operate directly on some or allof the parameters as stored over time in the capacity-relevant parameterlog 120 (FIG. 5A) and the battery capacity database 122 (FIG. 5C).Having said this, such direct analysis of the log 120 may be requiresignificance computational power, and thus the intermediate steps ofdetermining the present capacity-relevant parameters 120′ (FIG. 5B),populating the estimated capacity log 162 (FIG. 6C), etc. are preferred.

Referring again to FIG. 6A, once tEOL and tEOLi are forecasted, theirvalues can be stored in registers 126 and 124 (FIG. 4). Note that tEOLand tEOLi might have been forecasted and stored in registers 126 and 124upon a previous run of the algorithm 160. If desired, thenewly-forecasted (and presumably more accurate) values for tEOLi andtEOL can be added to registers 124 and 126 while still keeping oldervalues, or these older values can be overwritten.

At this point, algorithm may assess whether tEOLi has been determined,which can entail determining whether the current time is after tEOLi asforecasted. If not, the algorithm ends at this point, and the algorithmof FIG. 6A will continue to be used in the future, until tEOLi isdetermined. If so, the EOLi indicator bit 125 is set, which informs thealgorithm 160 that new values for tEOLi should not again be forecastedor stored in EOLi register 124 during future runs of the algorithm 160.Register 124 thus preserves the time at which EOLi was reached.

Once tEOLi is determined, the IPG 10 may hold tEOLi (124), the EOLiindicator (125), and/or the forecasted tEOL (126), and preferably all ofthese, in a manner flagging them as priority data to be sent to anexternal device once the external device initiates a communicationsession with the IPG 10, essentially in the same manner discussed withrespect to the tSDi indicator in the Background. Prior to determiningtEOLi, the algorithm 160 may not necessarily take steps to transmittEOLi or tEOL as forecasted to the external device, because batterycapacity is not yet of concern. Nonetheless, these forecasted values arestill stored (126, 124), and can be read from the IMD 10 at the commandof an external device.

The external device receiving these indications and relaying them to thepatient could comprise an external charger 90 (FIG. 2), in which casethese indications would be sent by LSK telemetry using LSK modulationcircuitry 45 (FIG. 2). As this means of telemetry is relatively simple,and because external chargers may have only simple user interfaces, onlythe EOLi indicator (125) may be telemetered. Upon receipt of the EOLiindicator, the external charger 90 can alert the user in any number ofways, such as by uniquely lighting LED(s) on the case of the externalcharger or “beeping” of the external charger's speaker.

Alternatively, a more-sophisticated device may initiate a communicationsession with the IMD 10, such as a patient external controller or aclinician's programmer. Such external devices typically have graphicaluser interfaces with displays, and so all of tEOLi, the EOLi indicator,and the tEOL forecast are preferably telemetered and indicated on thedisplay. As with the tSDi indicator discussed earlier, this can involvethe use of the IMD's telemetry coil 42 and associated telemetrycircuitry 43 (FIG. 2). Such means of telemetry may employ FrequencyShift Keying (FSK), and can occur via magnetic induction or by RadioFrequency telemetry (if the IMD 10 has an RF antenna; not shown).

If the external device receiving these indications has broaderconnectivity, such as to the Internet, or if the IMD 10 itself has suchconnectivity, such indications may also be sent to the patient'sclinician or to the manufacturer. As discussed earlier, the manufacturercould use such data to better understand their warranty and supportobligations, which may have changed from those otherwise specified as adefault (e.g., a 12-year warranty). For example, if warranty and supportare made contingent on tEOL, understanding when tEOL was determined oris forecasted to issue is beneficial for the manufacturer and/or itsservice representatives to know.

Once tEOLi is determined (e.g., bit 125 set), the algorithm of FIG. 6Ais not used in the future. Instead, future execution of the algorithm160 will occur as set forth in FIG. 7. As noted earlier, the portion ofthe algorithm set forth in FIG. 7 seeks to forecast (or update theforecast of) tEOL, and to assess whether tEOL has been determined andthus that EOL indication bit 127 can be set.

FIG. 7 is similar to FIG. 6A, although focusing on EOL only, EOLi havingalready been determined. Thus as shown, the algorithm 160 as beforeretrieves the capacity-relevant parameters logs 120/120′ and consultsthe battery capacity database 122; determines the percentage change foreach parameter; retrieves the weight/priority for each parameter ispresent and used; and processes those percentages to determine anestimated total percentage change to the battery capacity, which isstored in estimated capacity log 162. Forecasting/determinationalgorithm 164 again operates to forecast tEOL, which is stored inregister 126. (Note that algorithm 164 at this point need not considerthresholds relevant to EOLi, such as tGRACE (FIG. 6D) or Cap(th)(EOLi)(FIG. 6E). That is, only Cap(th) (FIG. 6D) or Cap(th)(EOL) (FIG. 6E) areused). If tEOL is not determined, the algorithm 160 ends and thealgorithm of FIG. 7 is used again until the tEOL determination is made.When tEOL is determined in the future, EOL indicator bit 127 is set, andtEOL (126) and/or its indication (127) are telemetered at one or morefuture communication or charging sessions. Once tEOL has beendetermined, the algorithm 160 has largely served its purpose, and itsuse may be discontinued.

As noted earlier, the shutdown time tSD and its early indicator tSDi maystill be included and used in the IMD 10 in conjunction with the tEOLiand tEOL forecasts and determinations provided by the EOL algorithm 160.Alternatively, tEOLi and tEOL may supplant the function of tSDi and tSD,and thus be used to indicate and shutdown operation of the IMD 10, inwhich case tSDi and tSD would be unnecessary.

It is still possible and perhaps preferable to include use of theshutdown time tSD in the improved IMD employing the EOL algorithm 160.One manner in which this can occur is shown in FIG. 8, which illustratesuse of a shutdown algorithm 170 for suspending therapeutic operation ofthe IMD 10. As shown in FIG. 4, the shutdown algorithm 170 receives tSDand tEOL from registers 115 and 126 as its inputs. Earlier indicators ofthese values, such as tSDi and tEOLi, are not necessary to consider, butcould be in other embodiments.

As shown, the shutdown algorithm 170 begins to operate when either tSDor tEOL are determined to have occurred. If tEOL has been assertedfirst, tSD would be later in time that tEOL (see strenuous-use IMDpatient A in FIG. 6D). In response, the shutdown algorithm 170preferably suspends therapeutic operation of the IMD 10. In effect, thedetermination of tEOL—i.e., the indication that the battery capacity hasnow degraded to an impermissible degree, and thus has truly reached itsend of life—trumps the preset value for tSD. As noted earlier, thisinformation, which may be wirelessly transmitted to the manufacturer,may operate to limit the manufacturer's warranty and serviceobligations.

In this scenario, there may be good reasons to override the shutdownalgorithm 170's ability to use tEOL to shut down therapeutic operationof the IMD, particularly if tSD has not been reached. For example, if anIPG patient is too ill to undergo an explanation procedure, it may bereasonable to continue to let the patient use the IMD, particularly ifit seems to be working adequately (despite exceeding tEOL). In thiscase, a clinician or the manufacturer could decide that the EOLalgorithm 160 should be overridden, i.e., that tEOL should be ignored bythe shutdown algorithm 170. The clinician or manufacturer could sooverride tEOL using their more-sophisticated external devices, whichunlike the patient external controller would have authority to accessand change operation of the EOL algorithm 160. Overriding tEOL may beparticularly reasonable in such special cases, particularly when onenotes that the computation of tEOL is based on assumptions, and thusthat tEOL does not perfectly predict end of IMD life.

If tSD has been asserted first at the start of the shutdown algorithm170, tEOL has not been determined, and is at this point merelyforecasted as stored in register 126 (see light-use IPG patient B inFIG. 6D). In this case, tEOL may suggest that the IMD is working finefor this patient (at least from a battery capacity perspective), andtherefore that it may be reasonable for the patient to continue to usethe IMD for a longer time.

If so, tSD may be adjusted to a later time by overwriting tSD inregister 115. In one simple option not illustrated, tSD could simply beadjusted to the forecasted value for tEOL, either automatically by theIPG, or by a clinician or manufacturer. However, because tEOL is merelya forecast resting on assumptions, such a strategy for adjusting tSD andextending IMD life runs the risk of placing tSD too far in the futurebeyond the time at which the IMD's life actually ends.

More conservative options for this scenario are thus illustrated in FIG.8. In one option, the IPG 10 itself can adjust tSD via the shutdownalgorithm 170. It is preferred that this option would only be used insituations where tEOL as forecasted is well beyond tSD, by 7 years inthe illustrated example. Should this criteria be met, the shutdownalgorithm 170 may increase tSD by some additional amount to allowtherapeutic use of the IMD to continue. In one example, tSD could beincreased by the full difference between tEOL as forecasted and tSD.This is akin to setting tSD to the forecasted tEOL, which as noted abovemay be of concern. Thus, a more preferred option would be to allow theshutdown algorithm 170 to automatically increase tSD by a lesser amount,such as 2 years as illustrated, or by some fraction of the fulldifference (e.g., k*(tEOL forecast−tSD), where 0<k<1). As noted above,should tSD be adjusted upwards in this manner, the manufacturer mayextend its warranty and support obligations. Alternatively, themanufacturer may still only warrant and support the IMD up to tSD. Ineffect, the patient could continue to use her IMD, but the manufacturermay thereafter be free of continued responsibility.

Another conservative option illustrated in the scenario where tSD hasbeen reached, but tEOL has not, is to simply suspend operation of theIMD. In effect, tSD trumps tEOL for safety or liability reasons.However, such suspension of operation may not be permanent, andtherapeutic operation can commence later pursuant to the discretion ofthe clinician or manufacturer. Even though the IMD is at this point notproviding stimulation therapy for example, it is still preferablycapable of powering housekeeping functions such as telemetry. Theclinician or manufacture may thus download data from the IMD for review,including the forecasted tEOL in register 126. Upon qualitative reviewof such data, including an understanding of the patient's history andneeds, the clinician or manufacturer may decide to adjust tSD inregister 115 (using an external clinician's programmer) by an amountwith which they are comfortable, such as 1.5 years in the illustratedexample. It would be expected that such increase would againconservatively less than the amount fully suggested by tEOL (asillustrated in this example, 5 years), for the reasons described above.And again, extending tSD may have warranty and support implications.

Although not illustrated, tSD may in some cases be adjustable downward(i.e., tSD in register 115 overwritten) to a lower time. This could beuseful if tEOL as forecasted would occur before TSD, such as in the caseof the strenuous-use IPG patient B.

It should be noted that the illustrated order of the steps performed inEOL algorithm 160 and the shutdown algorithm 170 are merely examples,and changes could be made to the disclosed order in manners notaffecting its overall results. Additionally, not all steps are strictlynecessary, and other steps could be included as well.

While algorithm 160 has been disclosed as forecasting and determiningboth tEOLi and tEOL, it should be noted that the algorithm 160 caninstead be used to forecast and determine one of these values. Likewise,algorithm 160 can also be used to only forecast these values withoutdetermining when they are reached, or only to determine when they arereached without forecasting.

While forecasting and determination of tEOLi and tEOL has beenillustrated for completeness as potentially involving analysis ofseveral different capacity-relevant parameters, which can be weighted,mathematically combined, etc. it should be noted that the use of even asingle capacity-relevant parameter reviewed over some portion of theIMD's life is sufficient to implement the disclosed EOL algorithm, andto determine and forecast tEOLi and tEOL in a rechargeable-battery IMD.

Although various logs, databases, registers, and algorithms in FIG. 4are shown as programmed into the memory of the microcontroller 100, theycould instead reside outside of the microcontroller 100 and madeaccessible to the EOL algorithm 160 and shutdown algorithm 170, whichwould typically operate in the microcontroller 100.

Although particular embodiments of the present invention have been shownand described, it should be understood that the above discussion is notintended to limit the present invention to these embodiments. It will beobvious to those skilled in the art that various changes andmodifications may be made without departing from the spirit and scope ofthe present invention. Thus, the present invention is intended to coveralternatives, modifications, and equivalents that may fall within thespirit and scope of the present invention as defined by the claims.

What is claimed is:
 1. Circuitry for a medical device, comprising: arechargeable battery; control circuitry configured to configured toimplement an algorithm, wherein the algorithm is configured to: estimatea capacity of the battery at different points in time during operationof the medical device, store the estimated capacities and theirassociated times in the medical device, and forecast and/or determine anend of life of the medical device by deriving a function of batterycapacity versus time using the stored estimated capacities and theirassociated times.
 2. The circuitry of claim 1, wherein the algorithmforecasts and/or determines the end of life in accordance with a firstcapacity threshold.
 3. The circuitry of claim 2, wherein the algorithmis further configured to forecast and/or determine an early indicator ofthe end of life.
 4. The circuitry of claim 3, wherein the earlyindicator comprises a set time before the forecasted end of life.
 5. Thecircuitry of claim 3, wherein the algorithm forecasts and/or determinesthe early indicator of the end of life in accordance with a secondcapacity threshold.
 6. The circuitry of claim 3, wherein the algorithmis further configured to store the forecasted and/or determined earlyindicator for transmission to an external device.
 7. The circuitry ofclaim 1, wherein the algorithm suspends therapeutic operation of themedical device when the end of life is determined.
 8. The circuitry ofclaim 1, wherein the algorithm is further configured to use theforecasted end of life to extend therapeutic operation of the medicaldevice beyond a shutdown time.
 9. The circuitry of claim 1, wherein thecontrol circuitry further comprises: memory configured to store at leastone parameter having an effect on a capacity of the rechargeablebattery, wherein the at least one parameter is selected from a groupconsisting of one or more parameters relevant to: previous charging ofthe battery, previous use of the medical device to provide therapy, andthe age of the battery; wherein the algorithm is configured to estimatethe capacity of the battery at the different points in time using the atleast one parameter.
 10. The circuitry of claim 9, wherein the at leastone parameter is stored as a function of time in the memory.
 11. Thecircuitry of claim 9, wherein the at least one parameter is stored as apresent value for use by the algorithm.
 12. The circuitry of claim 9,wherein the at least one parameter comprises a value computed from atleast one other parameter measured during previous charging of thebattery or previous use of the medical device.
 13. The circuitry ofclaim 9, wherein parameters relevant to previous charging of therechargeable battery comprise a number of previous charging session, avoltage of the battery at the start of a previous charging session, avoltage of the battery at the end of a previous charging session, aduration of a previous charging session, a charge provided to thebattery during a previous charging session, a discharge depth comprisinga difference between a voltage of the battery at the start and finish ofa previous charging session, and a battery charging current provided tothe battery during a previous charging session.
 14. The circuitry ofclaim 9, wherein parameters relevant to previous use of the medicaldevice to provide therapy comprise a voltage of the rechargeable batteryduring a previous use, a load current drawn from the battery during aprevious use, a power drawn from the battery during a previous use, aduration a use, and a charge drawn from the battery during a previoususe.
 15. The circuitry of claim 9, further comprising a battery capacitydatabase, wherein the battery capacity database associates the at leastone parameter with a change in the capacity of the battery, wherein thealgorithm compares the at least one parameter to a change in thecapacity in the battery capacity database to determine the capacity ofthe battery at the different points in time.
 16. The circuitry of claim9, wherein the memory further comprises a weight or priority of each atleast one parameter, wherein the algorithm is configured to determinethe capacity of the battery at the different points in time by using theweight or priority or both the weight and priority of the at least oneparameter.
 17. A method for operating a medical device having arechargeable battery, comprising: estimating and storing in the medicaldevice a capacity of the rechargeable battery of the medical device as afunction of time during operation of the medical device, and forecastingand/or determining an end of life of the medical device by extrapolatingfrom the capacity as a function of time a time at which the capacityequals a capacity threshold.
 18. Circuitry for a medical device,comprising: a rechargeable battery; a first register configured to storea shutdown time at which therapeutic operation of the medical devicewill be suspended; control circuitry configured to configured toimplement an algorithm, wherein the algorithm is configured to:determine an end of life of the medical device using at least a firstestimated capacity of the battery; and suspend therapeutic operation ofthe medical device even if the shutdown time has not been reached. 19.The circuitry of claim 18, wherein the algorithm is further configuredto resume therapeutic operation of the medical device upon receipt of anoverride.
 20. The circuitry of claim 18, wherein the algorithm isfurther configured to forecast an end of life of the medical deviceusing at least a second estimated capacity of the battery; determinethat the shutdown time has been reached; continue therapeutic operationof the medical device if the forecasted end of life is greater than theshutdown time; and suspend therapeutic operation of the medical deviceif the determined end of life is not greater than the shutdown time. 21.The circuitry of claim 20, wherein the algorithm is configured tocontinue therapeutic operation of the medical device by adjusting theshutdown time to a later time in the first register.
 22. The circuitryof claim 21, wherein the later time is between the shutdown time and theforecasted end of life.
 23. The circuitry of claim 21, wherein the latertime is of a fixed duration.
 24. Circuitry for a medical device,comprising: a rechargeable battery; a first register configured to storea shutdown time at which therapeutic operation of the medical devicewill be suspended; control circuitry configured to configured toimplement an algorithm, wherein the algorithm is configured to: forecastan end of life of the medical device using at least a first estimatedcapacity of the battery; determine that the shutdown time has beenreached; continue therapeutic operation of the medical device if theforecasted end of life is greater than the shutdown time; and suspendtherapeutic operation of the medical device if the determined end oflife is not greater than the shutdown time.
 25. The circuitry of claim24, wherein the algorithm is configured to continue therapeuticoperation of the medical device by adjusting the shutdown time to alater time in the first register.
 26. The circuitry of claim 25, whereinthe later time is between the shutdown time and the forecasted end oflife.
 27. The circuitry of claim 25, wherein the later time is of afixed duration.